Neurogrid: A mixed-analog-digital multichip system for large-scale brain simulationsKwabena Boahen - Stanford University

Biography:

Kwabena Boahen is an Associate Professor in the Bioengineering Department at Stanford University, where he directs the Brains in Silicon Lab. From 1997 to 2005 he was on the faculty of University of Pennsylvania, Philadelphia PA. He is a bioengineer who is using silicon integrated circuits to emulate the way neurons compute, linking the seemingly disparate fields of electronics and computer science with neurobiology and medicine. His lab is currently developing Neurogrid, a specialized hardware platform created at Stanford that simulates the cortex’s inner workings in real-time—something outside the reach of even the fastest supercomputers. Professor Boahen’s numerous contributions to the field of neuromorphic engineering include a silicon retina that could be used to give the blind sight and a self-organizing chip that emulates the way the juvenile brain wires itself up. His scholarship is widely recognized, with over eighty publications to his name, including a cover story in the May 2005 issue of Scientific American. He has received several distinguished honors, including a Fellowship from the Packard Foundation in 1999, a CAREER award from the National Science Foundation in 2001, a Young Investigator Award from the Office of Naval Research in 2002, and the National Institute of Health Director’s Pioneer Award in 2006.

Abstract:

Large-scale brain simulations link high-level cognitive phenomena to low-level biophysical mechanisms, helping neuroscientists understand how cognition emerges from the brain’s wetware. These simulations use a digital approach to model ion-channels that was pioneered by Hodgkin and Huxley in the 1940s. Computer performance has increased over a billionfold since then (Moore’s Law), enabling present-day super computers to simulate networks with millions of neurons connected by billions of synapses in real-time. This scale is only about 0.01% of the human cortex, however. And Moore’s Law has plateaued in recent years, putting real-time full-brain simulations out of reach for the foreseeable future—even for the fastest supercomputers. Fortuitously, with the recently developed ability to emulate (i.e., simulate in real-time) various types of ion-channels, the analog technique pursued by neuromorphic engineers over the past two decades has matured. The brain can now be modeled using subthreshold analog computation to emulate ion-channel activity and asynchronous digital communication to route synaptic connections. Neurogrid, an entirely clockless system with sixteen mixed-analog-digital chips created at Stanford, emulates a million cortical neurons connected by six billion synapses. It rivals the performance of 20 IBM Blue Gene racks on this particular task while consuming five orders of magnitude less energy. By providing an affordable platform to perform large-scale simulations, Neurogrid is helping neuroscientists vet various hypotheses about how the brain works.